The healthcare industry has been slow to join the information technology revolution; handwritten records are still the primary means of organizing patient care. Concerns about patient privacy, the difficulty of developing appropriate computing tools and information technology, high costs, and the resistance of some physicians and nurses have hampered the use of technology in health care. In 2009, the U.S. government committed billions of dollars to health care technology. Many questions remain, however, about how to deploy these resources.
Humans have modeled their technology on nature for centuries. The inventor of paper was inspired by a wasp’s nest; Brunelleschi demonstrated the principles of his famous dome with an egg; a Swiss company produced a wristwatch with an alarm modeled on the sound-producing capabilities of a cricket. Today, in the era of the “new bionics,” engineers aim to reproduce the speed and maneuverability of the red tuna in a submarine; cochlear implants send sound signals to the auditory nerve of a hearing-impaired person; and robots replicate a baby’s cognitive development.
Today the measurable health burden of neurological and mental health disorders matches or even surpasses any other cluster of health conditions. At the same time, the clinical applications of recent advances in neuroscience are hardly straightforward.
Ignorance and surprise belong together: surprises can make people aware of their own ignorance. And yet, perhaps paradoxically, a surprising event in scientific research—one that defies prediction or risk assessment—is often a window to new and unexpected knowledge.
Seeing has puzzled scientists and philosophers for centuries and continues to do so. This new edition of a classic text offers an accessible but rigorous introduction to the computational approach to understanding biological visual systems.
Biomedical signal analysis has become one of the most important visualization and interpretation methods in biology and medicine. Many new and powerful instruments for detecting, storing, transmitting, analyzing, and displaying images have been developed in recent years, allowing scientists and physicians to obtain quantitative measurements to support scientific hypotheses and medical diagnoses. This book offers an overview of a range of proven and new methods, discussing both theoretical and practical aspects of biomedical signal analysis and interpretation.
In the six decades since the publication of Julian Huxley's Evolution: The Modern Synthesis, spectacular empirical advances in the biological sciences have been accompanied by equally significant developments within the core theoretical framework of the discipline. As a result, evolutionary theory today includes concepts and even entire new fields that were not part of the foundational structure of the Modern Synthesis.
This classic work by Julian Huxley, first published in 1942, captured and synthesized all that was then known about evolutionary biology and gave a name to the Modern Synthesis, the conceptual structure underlying the field for most of the twentieth century. Many considered Huxley's book a popularization of the ideas then emerging in evolutionary biology, but in fact Evolution: The Modern Synthesis is a work of serious scholarship that is also accessible to the general educated public.
Computational systems biology aims to develop algorithms that uncover the structure and parameterization of the underlying mechanistic model—in other words, to answer specific questions about the underlying mechanisms of a biological system—in a process that can be thought of as learning or inference. This volume offers state-of-the-art perspectives from computational biology, statistics, modeling, and machine learning on new methodologies for learning and inference in biological networks.
In recent years an interest in applying the principles of evolution to the study of culture emerged in the social sciences. Archaeologists and anthropologists reconsidered the role of innovation in particular, and have moved toward characterizing innovation in cultural systems not only as a product but also as an evolutionary process.
Why our dependence on coal-produced energy is bad for our health: a physician maps the connections of burning coal to death and disease.
An argument against the “lifeboat ethic” of contemporary bioethics that views medicine as a commodity rather than a tradition of care and caring.
Lynn MargulisCeleste A. AsikainenScientists elucidate the astounding collective sensory capacity of Earth and its evolution through time.
Two leading physicians’ prescription for solving our health care problems: organizing the fragmented system that delivers care.
Jeremy R. GarrettA balanced, accessible discussion of whether and on what grounds animal research can be ethically justified.
Lynn MargulisCeleste A. Asikainen
Jeremy R. Garrett
